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Each table includes the optimal weights, mean errors and standard deviations for the relevant error measures, and the MSE and MAE for the optimal convex estimator.
The mean errors, and and associated variances, and are also indicated, as they build the basic descriptors of the computed distributions.
Results of the tests indicate that the mean errors and variances of errors of the modelling based on the neural fuzzy networks approach are all better than those of the other existing approaches, statistical regression, fuzzy regression and neural networks, on modelling the fluid dispensing.
In similar to Remark 4.5, for a suitable and appropriate choice of the sequences { e n, i } n = 0 ∞, { l n, i } n = 0 ∞ and { r n, i } n = 0 ∞ ( i = 1, 2, …, p ), Algorithms 6.1-6.5 6.1-6.5to algoreduce wito mealgorithmsand without errors.
The B97-D/TZVP case represents a favorable example with small mean errors and relatively tight error distributions (see Table 1 for other examples), but it would be computationally intractable to use it to study hundreds or thousands of decoys for a system of the size of ubiquitin.
To obtain the accuracy of the performed technique, mean errors and standard deviations were calculated for all translations and rotations.
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Figure 6 Mean error and mean squared error of the CFO estimation.
Figure 7 Mean error and mean squared error of the STO estimation.
The root mean squared error, mean error and mean absolute error calculated from leave-one-out cross-validation were used to assess prediction accuracy.
The mean error, absolute mean error and absolute relative mean error for each comparison are also calculated and given in Table 2.
The medium resolution shows the best agreement in terms of mean error and standard deviation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com